LAFe: Learning Analytics Solutions to Support On-Time Feedback
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Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Science and Business Media Deutschland GmbH
Abstract
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Feedback given to students by instructors is essential to guide students and help them improve from their mistakes. However, in higher education, instructors feel unable to give quality and timely feedback due to work overload and lack of time. In this context, this tutorial intends to discuss possible data-based and AI solutions for supporting students and instructors in the feedback process. It will include: a panel discussion about the importance of automating the feedback process, a demo of tools for this goal, and a card sorting activity to understand important aspects of developing tools to support on-time feedback.
Description
Keywords
Feedback tools, Provision of feedback using artificial intelligence, qualitative research